Be sure to show you setups for all the problems
7. Predict the number of Cars through the gate if the price is $8 and the average December temperature is 30 degrees.
|
Dependent Variable |
CARS |
|
N |
15 |
|
Multiple R |
0.8298604 |
|
Squared Multiple R |
0.6886683 |
|
Adjusted Squared Multiple R |
0.6647197 |
|
Standard Error of Estimate |
478.7469853 |
|
Regression Coefficients B = (X'X)-1X'Y |
||||||
|
Effect |
Coefficient |
Standard Error |
Std. Coefficient |
Tolerance |
t |
p-value |
|
CONSTANT |
7,553.2334688 |
580.7547678 |
0.0000000 |
. |
13.0058914 |
0.0000000 |
|
PRICE |
-633.9414634 |
118.2181417 |
-0.8298604 |
1.0000000 |
-5.3624719 |
0.0001292 |
|
Dependent Variable |
CARS |
|
N |
15 |
|
Multiple R |
0.9203313 |
|
Squared Multiple R |
0.8470097 |
|
Adjusted Squared Multiple R |
0.8215113 |
|
Standard Error of Estimate |
349.3071128 |
|
Regression Coefficients B = (X'X)-1X'Y |
||||||
|
Effect |
Coefficient |
Standard Error |
Std. Coefficient |
Tolerance |
t |
p-value |
|
CONSTANT |
5,017.0284102 |
835.1434178 |
0.0000000 |
. |
6.0073854 |
0.0000615 |
|
PRICE |
-613.3296817 |
86.4533074 |
-0.8028786 |
0.9954233 |
-7.0943461 |
0.0000126 |
|
PITTDECT |
73.4854826 |
20.8519046 |
0.3988350 |
0.9954233 |
3.5241617 |
0.0041912 |
|
Case |
CARS |
PRICE |
PITTDECT |
|
1 |
6000 |
3 |
33.9 |
|
2 |
5966.7 |
3 |
31.7 |
|
3 |
4697.3 |
4 |
38.2 |
|
4 |
4436.8 |
4 |
27.7 |
|
5 |
4760 |
4 |
36.5 |
|
6 |
5072.8 |
4 |
33.5 |
|
7 |
5066 |
5 |
37.8 |
|
8 |
4446 |
5 |
34.6 |
|
9 |
3455.4 |
5 |
23.1 |
|
10 |
4781.4 |
5 |
37.5 |
|
11 |
3865.3 |
6 |
30.7 |
|
12 |
3447.8 |
6 |
32.6 |
|
13 |
3711 |
6 |
33.3 |
|
14 |
3448.2 |
6 |
27.6 |
|
15 |
4500.2 |
6 |
38.8 |
|
16 |
. |
. |
. |
Be sure to show you setups for all the problems Examine the computer output for Equation...
Problem 5- Simple Linear Regression The following data represent the number of flash drives sold per day at a local computer shop and their prices Price $34 36 32 35 30 Units Sold 6 40 A computer output is produced to examine this relationship further SUMMA RY OUTPUT Regression Statistics Multiple R RSquare Adjusted R Square Standard Error Observations 0.924982 0.855592 0.826711 1.119949 7 ANOVA MS gnificance F Regression Residual Total 137.15714 37.15714 29.62415 0.002842 5 б,271429 1.254286 6 43.42857...
show all steps, excel not allowed, thank you and will rate
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.989778267 0.979661017 0.969491525 0.387298335 4 ANOVA Significance F 14.45 96.33333 0.010221733 MS Regression Residual Total 14.45 0.3 14.75 0.15 Coefficients p-value Lower 95% U per 95% Lower 95.096 Upper 95.0% 7 0.474341649 14.75729575 0.00456 4.959072609 9.040927 4.959072609 9.040927391 1.7 0.173205081-9.814954576 0.010222 -2.445241314 0.95476-2.445241314 -0.954758686 Standard Errort Stat Intercept Case Sales a. Write the regression equation for the...
Please show work so that I can see the process also Let’s say you scored a 111 on exam 1 and you scored an 125 on exam 2. You can predict your final exam score with the following prediction equation: Y’ = bX + c (round to nearest whole number). X is the total number of points you earned on the first two tests. Given: Mean = 120; standard deviation of y = 100. The correlation (r) between the total...
24. United Widget Manufacturing has a problem with defective widgets. Employees make hundreds of thousands of them each day, and many are defective. United has instituted training for the workers, and you would like to predict the number of defects per week based on the number of days of training an employee has received. You obtain the following data: ST Employee number 1015 2023 1153 4029 1117 0012 Days of training 4 5 6 4 3 2 Defects per week...
Hello I need help with questions 2 until 9 if possible. If you
can please show all work and answers clearly. Thanks for all the
help have this project that’s due tonight so I need help on
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27 27889.0526471 10.12 1.09 28 SUMMARY OUTPUT 29 30 Regression Statistics 1 Multiple F 0.986442 32 R Square 0.973068 33 Adjusted 0.967681 34 Standard I 32.55341 35 Observati 36 37 ANOVA 38 39 Regressio 40 Residual 41 Total 42 43 44 Intercept...
"By Hand" Problems: For hypothesis tests, you may use R to find the p-value. For confidence intervals, you may use R to find the multiplier 1. (Continuation of HW 7, Problem 3) Suppose it is of interest to examine the relationship between the size of cruise chips and their passenger capacity. A data from 158 cruise ships was collected based on the following two variables: . Size of the ship (Tonnage) the gross tonnage in 1000s of tons Maximum passenger...
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Statistical Analysis: The regression output presented on the next page was obtained from regressing the dependent variable Y on the independent variable L. The variable Y is real gross domestic product measured in billions of year 2009 dollars. The labor variable L is the number of full time equivalent employees measures in thousands of employees 5. Present these regression results in a professional manner, as demonstrated in class. (10 points) Provide an economic interpretation of...
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15. United Widget Manufacturing has a problem with defective widgets. Employees make hundreds of thousands of them each day, and many are defective. United has instituted training for the workers, and you would like to predict the number of defects per week based on the number of days of training an employee has received. You obtain the following data: Employee number 1015 2023 1153 40291117 0012 Days of training 4. 5 6 4 3 2 Defects per week (100s) 19...
Please show all work need help with ALL parts part of one question
Assignment 3 [Read-Onlyl Word View ? Tell me Share File Home Insert Design Layout References Mailings Review Outline Draft New WindowE Arrange All Switch Macros Properties Windows Web Side Show Zoom 100% Read ode Layout Layout Learning Tools to Side Split Macros SharePoint Views Immersive Page Movement Part (b) (2 points) Interpret the estimated value of the intercopt, i.e,explain what the number means in this regression Part...